Finite Mixture and Markov Switching Models
This book should help newcomers to the field to understand how finite mixture andMarkov switching models are formulated, what structures they imply on the data, what they could be used for, and how they are estimated. Researchers familiar with the subject also will profit from reading this book. The...
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| Format: | eBook |
| Language: | English |
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New York, NY
Springer New York
2006, 2006
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| Edition: | 1st ed. 2006 |
| Series: | Springer Series in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Finite Mixture Modeling
- Statistical Inference for a Finite Mixture Model with Known Number of Components
- Practical Bayesian Inference for a Finite Mixture Model with Known Number of Components
- Statistical Inference for Finite Mixture Models Under Model Specification Uncertainty
- Computational Tools for Bayesian Inference for Finite Mixtures Models Under Model Specification Uncertainty
- Finite Mixture Models with Normal Components
- Data Analysis Based on Finite Mixtures
- Finite Mixtures of Regression Models
- Finite Mixture Models with Nonnormal Components
- Finite Markov Mixture Modeling
- Statistical Inference for Markov Switching Models
- Nonlinear Time Series Analysis Based on Markov Switching Models
- Switching State Space Models